Chapter 3 - Design methodologies for conventional and additive manufacturing

Design for manufacture and assembly (DfMA) in the architectural, engineering, and construction (AEC) industry is attracting the attention of designers, practitioners, and construction project stakeholders. Digital fabrication (Dfab) and design for additive manufacturing (DfAM) practices are found in current need of further research and development. The DfMA’s conceptual function is to maximize the process efficiency of Dfab and AM building projects. This work reviewed 171 relevant research articles over the past few decades. The concepts and the fundamentals of DfMA in building and construction were explored. In addition, DfMA procedures for Dfab, DfAM, and AM assembly processes were discussed. Lastly, the current machine learning research on DfMA in construction was also highlighted. As Dfab and DFAM are innovated, practical DFMA techniques begin to develop to a great extent. Large research gaps in the DfMA for Dfab and DfAM can be filled in terms of integrating them with product structural performance, management, studied cases, building information modeling (BIM), and machine learning to increase operational efficiency and sustainable practices.

Additive manufacturing (AM) has impacted the manufacturing of complex three-dimensional objects in multiple materials for a wide array of applications. However, additive manufacturing, as an upcoming field, lacks automated and specific design rules for different AM processes. Moreover, the selection of specific AM processes for different geometries requires expert knowledge, which is difficult to replicate. An automated and data-driven system is needed that can capture the AM expert knowledge base and apply it to 3D-printed parts to avoid manufacturability issues. This research aims to develop a data-driven system for AM process selection within the design for additive manufacturing (DFAM) framework for Industry 4.0. A Genetic and Evolutionary Feature Weighting technique was optimized using 3D CAD data as an input to identify the optimal AM technique based on several requirements and constraints. A two-stage model was developed wherein the stage 1 model displayed average accuracies of 70% and the stage 2 model showed higher average accuracies of up to 97.33% based on quantitative feature labeling and augmentation of the datasets. The steady-state genetic algorithm (SSGA) was determined to be the most effective algorithm after benchmarking against estimation of distribution algorithm (EDA) and particle swarm optimization (PSO) algorithms, respectively. The output of this system leads to the identification of optimal AM processes for manufacturing 3D objects. This paper presents an automated design for an additive manufacturing system that is accurate and can be extended to other 3D-printing processes.

As a new manufacturing method, Additive Manufacturing has begun to get a foothold in the manufacturing industry. The effective exploitation of the technology requires many times a re-design of the product or re-considering the manufacturing technology. Design for additive manufacturing differs considerably from design to other manufacturing methods, therefore design guidelines for additive manufacturing has been developed. The purpose of this paper is to present a new variant of the Design for Manufacturing and Assembly (DFMA) method which supports additive manufacturing.

The vertical lunchbox (VL) project, propose an innovative and functional solution for movement. Traditional lunchboxes often fail to meet the diverse needs of today’s consumers, including the desire for convenience, portability, and meal freshness. This project uses the advantages of additive manufacturing to create a lunchbox that not only offers practicality and usability but also incorporates distinctive features tailored to present lifestyles. The design process employs a concept of Design for Additive Manufacturing (DfAM) and Design for Manufacturing and Assembly (DfMA) principles. These concepts enable the development of required features and at the same time reducing assembly time and improve the functionality. Important features of the vertical lunchbox include customizable compartments that can accommodate ice packs, the lid that can be used as a handphone holder, and removable containers for easy cleaning. These features are catering to the needs of busy professionals and students. Parametric modeling and topological optimization helped to ensure that the lunchbox design is appealing and at the same time lightweight and strong. The adoption of 3D printing technology enabled faster production processes with required dimensional accuracy. Test results indicate that the vertical lunchbox meets most of the user requirements. The important features such as a secured locking and snap-fit lid design ensured the reliable transport containers for carrying food. In Addition, the project proved that additive manufacturing can be used for time to market approach of the product development. Finally, the vertical lunchbox project demonstrates how advanced manufacturing techniques can transform traditional product design to meet modern consumer needs.

A building faces several challenges across its lifecycle stages. Challenges such as production inefficiency and inadequate waste management hinder advancement in the construction industry. Furthermore, the sector has emerged as one of the largest producers of waste in the world, which can lead to detrimental impacts on the economy and the environment. Conventional approaches are insufficient to eradicate these concerns. Thus, practitioners have sought to implement novel methods to ameliorate the construction process. In this regard, design for manufacturing and assembly (DfMA) and design for deconstruction (DfD) have gained prominence, as studies have elucidated the methods’ unprecedented potential to wholly transform the construction process and mitigate the unwanted impacts brought about by the industry. This study identified the applications and benefits of DfMA and DfD in construction, as well as recent developments and research gaps, through a literature review, using Scopus as the primary database and MATLAB for conducting data text analytics. The current body of knowledge necessitates a further assessment of the following research gaps: (1) development of standard construction-oriented DfMA guidelines; (2) corroboration of the developed DfMA tools through practical application; (3) integration of these holistic design approaches with emerging technologies, such as additive manufacturing and digital fabrication; (4) comparison of structures constructed using DfMA and DfD with structures built with conventional approaches; (5) comprehensive application of DfD guidelines to structural systems; (6) integration of DfMA and DfD; (7) execution of sustainability assessment studies to evaluate the impact of DfMA and DfD; and (8) identification of solutions to the barriers to DfMA and DfD uptake in construction.

Chapter 1 - Overview of additive manufacturing technology and materials

Additive manufacturing (AM) processes have many benefits for the fabrication of alloy parts, including the potential for greater microstructural control and targeted properties than traditional metallurgy processes. To accelerate utilization of this process to produce such parts, an effective computational modeling approach to identify the relationships between material and process parameters, microstructure, and part properties is essential. Development of such a model requires accounting for the many factors in play during this process, including laser absorption, material addition and melting, fluid flow, various modes of heat transport, and solidification. In this paper, we start with a more modest goal, to create a multiscale model for a specific AM process, Laser Engineered Net Shaping (LENS™), which couples a continuum-level description of a simplified beam melting problem (coupling heat absorption, heat transport, and fluid flow) with a Lattice Boltzmann-cellular automata (LB-CA) microscale model of combined fluid flow, solute transport, and solidification. We apply this model to a binary Ti-5.5 wt pct W alloy and compare calculated quantities, such as dendrite arm spacing, with experimental results reported in a companion paper.

The design methodologies and part shape algorithms for additive manufacturing (AM) are rapidly growing fields, proven to be of critical importance for the uptake of additive manufacturing of parts with enhanced performance in all major industrial sectors. The current trend for part design is a computationally driven approach where the parts are algorithmically morphed to meet the functional requirements with optimized performance in terms of material distribution. However, the manufacturability restrictions of AM processes are not considered at the primary design phases but at a later post-morphed stage of the part’s design. This paper proposes an AM design method to ensure: (1) optimized material distribution based on the load case and (2) the part’s manufacturability. The buildability restrictions from the direct energy deposition (DED) AM technology were used as input to the AM shaping algorithm to grant high AM manufacturability. The first step of this work was to define the term of AM manufacturability, its effect on AM production, and to propose a framework to estimate the quantified value of AM manufacturability for the given part design. Moreover, an AM design method is proposed, based on the developed internal stresses of the build volume for the load case. Stress tensors are used for the determination of the build orientation and as input for the part morphing. A top-down mesoscale geometric optimization is used to realize the AM part design. The DED Design for Additive Manufacturing (DfAM) rules are used to delimitate the morphing of the part, representing at the same time the freeform mindset of the AM technology. The morphed shape of the part is optimized in terms of topology and AM manufacturability. The topology optimization and AM manufacturability indicator (TMI) is introduced to screen the percentage of design elements that serve topology optimization and the ones that serve AM manufacturability. In the end, a case study for proof of concept is realized.

Angle grinder use in grinding a product and for high performances application, like deburring in foundries and construction. Consequently, this study investigates about the sustainability design of angle grinder with integration of Design for Manufacturing and Assembly (DFMA) analysis. Design for Manufacturing and Assembly (DFMA) is a process that produce a good product which is minimize complexity and number of part that lead to time and cost reduction in development. Sustainability design means a design solution that are advantageous to both human and nature in a complete and combined way. Sustainability design in this research include the production and assembly part which is analysis using DFMA method. The design solutions are minimizing the part number and assembly time problem regardless the costs, materials issues and selection of manufacturing process. Using the DFE method combined with Boothroyd and Geoffrey DFMA principle, the analysis on angle grinder by using the 3D scanning method in drawing some part using the Catia software and the sustainability analysis using Solidwork software is done. The result for current product efficiency is 21.3% with 15.34 KgCO2, 2.10×10−2 KgPO4, 15.5 KgSO2, 1.95 MJ produce in producing one angle grinder. Through this study, expecting 25% of reduction in all criteria study.

Di zaman yang serba modern ini, sudah banyak alat pengayak pasir inovasi-inovasi baru yang diciptakan untuk memudahkan penggunanya dalam aktivitas sehari-hari. Akan tetapi, banyak produsen pengayak pasir yang fokus tertuju kepada produk yang efektif dan efisien. Banyak pekerja bangunan yang mengalami ke capekan dan ketidak nyamanan yang membutuhkan inovasi produk lebih dari pengayak pasir saat ini. Sementara itu pada saat ini tidak ada alat pengayak pasir yang efektif dan efisien dengan harga yang terjangkau. Pengayak pasir ini juga dirancang untuk mengurangi jumlah tenaga kerja, sehingga produk ini memiliki nilai tambah di masyarakat. Untuk mewujudkan tujuan itu digunakan metode Design For Manufacturing And Assembly (DFMA). Design For Manufacturing And Assembly (DFMA) adalah suatu metode untuk perancangan dan pengembangan produk. Design For Manufacturing And Assembly (DFMA) juga didefinisikan oleh sebagai suatu metode terstuktur untuk melakukan perancangan dan pengembangan produk sesuai yang diinginkan oleh konsumen serta mengevaluasi secara sistematis kapabilitas suatu produk atau jasa untuk memenuhi kebutuhan konsumen dan didapat hasil pengembangan produk menjadi lebih efektif dalam hal efisiensi, efektivitas, dan reliabilitas.

Purpose Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively. Design/methodology/approach The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process. Findings To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages. Originality/value This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

The additive manufacturing (AM) methods are being used to develop products using metals, ceramics and polymers with techniques such as layer-by-layer construction and filament deposition. Aside from the accuracy of the specific AM techniques, the broadcast elements must be inspected in order to be enforced within the target applications. The properties such as surface roughness, porosity, residual stress, and linkage are mainly used to finalize the components developed using AM. Furthermore, significant mechanical properties such as surface roughness, microstructures, hardness, tensile energy, compressive energy, fatigue, creep, and residual strain must be investigated on printed metal parts. The parameters of the AM strategies are designed to examine their effects on mechanical properties. The relationships between the AM process, parameters, and materials are interconnected to investigate the mechanical properties of AM components. The various AM techniques for printing metal components are properly classified along with their process parameters. Furthermore, various mechanical tests for metal-based components are detailed using ASTM guidelines. Based on the findings of this study, powder bed fusion techniques are recommended for the development of metal-based components due to their favorable factors for achieving better mechanical properties.

Recently, additive manufacturing (AM) has been a useful technology to fabricate complex parts. However, more consideration and technological developments are required for the expansion of the AM process in various industries. In particular, verification for repeatability and reproducibility of AM parts are very difficult issues when the AM parts are used in specific industries, such as nuclear and aerospace. In this respect, the change in the mechanical properties according to the relationship between AM parameters, machines, and powders is a very important area of research. In this study, four different L-PBF machines and three different powders from different suppliers were used to fabricate stainless steel 316L AM materials using same or similar AM parameters. In addition, tensile tests were conducted on all AM materials to obtain mechanical properties. The test results confirmed that differences in the mechanical properties were observed in the same AM process parameters of different machines and powder conditions.

This paper attempts to clarify the questions posed by the Boothroyd Dewhurst Inc. (BDI) design for manufacture and assembly (DFMA) methodology; namely those regarding: (1) part symmetry (alpha and beta), (2) relative movement, (3) different materials, and (4) possible assembly/disassembly constraints. Based on the authors' combined experience using the methodology and advising students; the questions, while simply posed and seemingly straightforward, can have subtle logical problems. Where possible, specific suggestions are offered for the questions addressed and in other cases the nature of any subtle problems is identified. It is hoped that the paper will serve as stimulus for the DFMA community to fully resolve the issues raised.

Additive manufacturing (AM) systems present tremendous advantages over the traditional manufacturing systems, particularly for realizing complex shapes and producing custom parts. These advantages, and the rapid growth in the availability of AM systems, have led to a widespread increase in the use of AM. Unfortunately, general design for additive manufacturing (DfAM) tools that predict the engineering performance of AM parts are largely unavailable, and this has forced engineers to rely on engineering judgment and/or data from physical experiments. The data sets reported in the literature that quantify the performance of the existing AM systems provide much needed insight, but the data produced by experiments conducted on specific AM systems are necessarily of limited applicability. Given the large number of AM systems currently in use today, a potentially vast amount of data are needed to fully understand them all, and new AM systems and materials are being developed almost daily. To mitigate this need for an ever-increasing amount of data, this paper proposes the use of an approximation-assisted multi-objective optimization technique to quantify the performance of an AM system for specific design application in a targeted fashion. This general approach uses a limited number of physical experiments to answer a specific DfAM question of interest, and the results can then be used to design functional parts without the need for additional data. The implementation of the proposed approach is demonstrated with a material extrusion case study.